Editing Mechanistic Interp (section)

== <span style="color: #FFFFFF;">Creating</span> ==
Starting mechanistic interpretability research:
# Begin with toy models (2-layer attention-only transformers) — fully analyzable.
# Use TransformerLens for GPT-2 scale; analyze induction heads following Olsson et al.
# .
# Formulate a falsifiable hypothesis about what a circuit does.
# Validate with activation patching — the gold standard causal test.
# Train sparse autoencoders on intermediate activations; analyze recovered features.
# Document findings rigorously, including negative results — the field needs honest failure reports as much as successes.

[[Category:Artificial Intelligence]]
[[Category:AI Safety]]
[[Category:Interpretability]]
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